Genetic tests to determine risk for monogenic diseases (such as cystic fibrosis or Huntington’s Disease) that are caused by a single mutation have been in use for over a decade. However, determining risk for complex diseases, which can be caused by hundreds to thousands of genetic variants that act in conjunction with environmental factors, remains challenging.
Polygenic risk scores (also known as polygenic scores and genetic risk scores) represent the total number of genetic variants that an individual has to assess their heritable risk of developing a particular disease. While there is still much more work needed to realize the potential for polygenic risk scores in precision medicine, polygenic risk scores have the potential to impact complex disease research and healthcare in a variety of ways:
In the first chapter of this series, experts explain what a polygenic risk score is and how they’re relevant to complex diseases.
Geneticists share key considerations researchers should think about when developing a polygenic risk score.
Learn more about future uses for polygenic risk scores, from stratifying populations to early intervention and preventative medicine.
Watch leading geneticists and professors share their insights about how polygenic risk scores can be used to predict an individual’s risk of complex disease.
Researchers perform genome-wide association studies to identify disease-associated DNA risk loci and develop scores for clinical validation.
Polygenic risk scores summarize genome-wide genotype data into a single number that represents genetic liability to a trait. Read this guide to learn more.
Explore how polygenic risk scores are developed, from design to validation, and learn which additional reporting and quality aspects to consider for your research.
Polygenic risk scores can provide researchers and physicians valuable insight into how predictive biomarkers for a specific complex disease can stratify patient populations according to risk. A study published by Khera, et al. in 2018 examined genome-wide polygenic risk scores in a population of over 250,000 individuals in the UK Biobank.1 They found 8% of the population tested had polygenic risk scores that conferred ≥ threefold increased risk for coronary artery disease.
This is a great example of how polygenic risk scores can be used by clinicians to stratify patients according to risk and identify individuals who would most benefit from additional monitoring or early preventative measures to offset the risk of disease.
Similar to polygenic risk scores, the field of pharmacogenomics benefits from genome-wide association studies to predict an individual’s response or ability to metabolize a drug or therapeutic. This provides valuable insights and has the potential to allow for tailored medications and dosages for patients.